um cuidado especializado do enfermeiro obstetra

Observa-se, hoje em dia, que algumas práticas na maternidade tendem a ignorar as preferências das mulheres em trabalho de parto, uniformizando os cuidados com prejuízo para o bem-estar e a qualidade de vida das famílias. As práticas em Obstetrícia têm vindo a tornar-se cada vez mais repletas de intervenção, focando-se apenas nos resultados físicos (mortalidade e morbilidade) e descurando as vivências das parturientes e família, assim como as consequências psicossociais de um parto traumático. O presente Relatório de Estágio pretende refletir os cuidados em maternidade na perspetiva EEESMOG, que se visa holística, centrada no cliente e baseada na evidência. Da mesma forma, espelha as aprendizagens efetuadas em contexto do Estágio com Relatório inserido no 6º CMESMO da ESEL. Foram escolhidos como referenciais teóricos norteadores os modelos de Nola Pender – Modelo de Promoção da Saúde, e a Teoria de Empowerment em Saúde de Nelma Shearer. Foi também realizada uma Revisão Sistemática da Literatura que visou responder à seguinte questão de investigação: “Quais os cuidados do EEESMOG promotores do empowerment das mulheres direcionado para uma tomada de decisão informada relativa ao trabalho de parto?”. Adicionalmente, foi efetuado um registo da interação durante a prestação de cuidados no decorrer do estágio, sobre os quais foi efetuada uma reflexão e confrontação com os resultados da RSL. Concluiu-se que os cuidados que o EEESMOG presta que são promotores de uma tomada de decisão informada para o trabalho de parto se inserem dentro de três grandes temas, nomeadamente Competências da esfera relacional, Competências da esfera da prática clínica e Competências da esfera científica, com especial referência para os cuidados que se relacionam com o Estabelecimento de Relação Terapêutica, a Educação para a Saúde, o Cuidado da Mulher em trabalho de parto, a Promoção do exercício do Consentimento Informado e a Prática baseada na Evidência

TARGETgene: A Tool for Identification of Potential Therapeutic Targets in Cancer

<div><p>The vast array of in silico resources and data of high throughput profiling currently available in life sciences research offer the possibility of aiding cancer gene and drug discovery process. Here we propose to take advantage of these resources to develop a tool, TARGETgene, for efficiently identifying mutation drivers, possible therapeutic targets, and drug candidates in cancer. The simple graphical user interface enables rapid, intuitive mapping and analysis at the systems level. Users can find, select, and explore identified target genes and compounds of interest (e.g., novel cancer genes and their enriched biological processes), and validate predictions using user-defined benchmark genes (e.g., target genes detected in RNAi screens) and curated cancer genes via TARGETgene. The high-level capabilities of TARGETgene are also demonstrated through two applications in this paper. The predictions in these two applications were then satisfactorily validated by several ways, including known cancer genes, results of RNAi screens, gene function annotations, and target genes of drugs that have been used or in clinical trial in cancer treatments. TARGETgene is freely available from the Biomedical Simulations Resource web site (<a href="http://bmsr.usc.edu/Software/TARGET/TARGET.html">http://bmsr.usc.edu/Software/TARGET/TARGET.html</a>).</p> </div

TARGETgene.

<p>A. The architecture design. B. The main graphical user interface.</p

ROC curve performance evaluation for predictions in the example 1.

<p>True positive rate is denoted TPR and false positive rate is denoted FPR in the Figure. A. Evaluation using curated cancer genes. B. Evaluation using genes cited by cited by cancer literature with different citation number cutoff values of 1, 5 and 10 (only the case of breast cancer is shown). C. Evaluation using target genes detected by cell viability RNAi screens.</p

ROC curve performance evaluation for predictions in the example 2.

<p>TARGETgene prediction performance is evaluated by genes in the identified core pathways.</p

Selected Drugs Whose Targets Are Highly-Ranked (the case of Breast Cancer).

<p><b>Note</b>: 1.Approved drugs are denoted as ‘A’.</p><p>2.Experimental compounds are denoted as ‘E’.</p><p>3.Drugs have been approved for the treatment of Breast Cancer are marked with ***.</p><p>4.Drugs in clinical trials for Breast Cancer are marked with *.</p

Additional file 4: Figure S2. of A multicenter, randomized study of decitabine as epigenetic priming with induction chemotherapy in children with AML

Distribution of differentially methylated loci (DML) according to functional CpG contextual distribution in Arms A (decitabine + chemotherapy) and B (chemotherapy alone). Pie charts demonstrate the frequency by which hyper or hypomethylated loci are distributed according to their functional position. (TIFF 443 kb

Additional file 2: Figure S1. of A multicenter, randomized study of decitabine as epigenetic priming with induction chemotherapy in children with AML

Schema of sample analysis workflow. (TIFF 269 kb

The Genomic Landscape of the Ewing Sarcoma Family of Tumors Reveals Recurrent <i>STAG2</i> Mutation

<div><p>The Ewing sarcoma family of tumors (EFT) is a group of highly malignant small round blue cell tumors occurring in children and young adults. We report here the largest genomic survey to date of 101 EFT (65 tumors and 36 cell lines). Using a combination of whole genome sequencing and targeted sequencing approaches, we discover that EFT has a very low mutational burden (0.15 mutations/Mb) but frequent deleterious mutations in the cohesin complex subunit <i>STAG2</i> (21.5% tumors, 44.4% cell lines), homozygous deletion of <i>CDKN2A</i> (13.8% and 50%) and mutations of <i>TP53</i> (6.2% and 71.9%). We additionally note an increased prevalence of the <i>BRCA2</i> K3326X polymorphism in EFT patient samples (7.3%) compared to population data (OR 7.1, p = 0.006). Using whole transcriptome sequencing, we find that 11% of tumors pathologically diagnosed as EFT lack a typical EWSR1 fusion oncogene and that these tumors do not have a characteristic Ewing sarcoma gene expression signature. We identify samples harboring novel fusion genes including <i>FUS-NCATc2</i> and <i>CIC-FOXO4</i> that may represent distinct small round blue cell tumor variants. In an independent EFT tissue microarray cohort, we show that STAG2 loss as detected by immunohistochemistry may be associated with more advanced disease (p = 0.15) and a modest decrease in overall survival (p = 0.10). These results significantly advance our understanding of the genomic and molecular underpinnings of Ewing sarcoma and provide a foundation towards further efforts to improve diagnosis, prognosis, and precision therapeutics testing.</p></div

Mutational frequency of recurrently altered genes in Ewing sarcoma family tumors and cell lines.

<p>*4 cell lines were tested only for <i>STAG2</i> mutation but not <i>TP53</i> nor <i>CDKN2A</i>.</p